Dynamic State Changes Research Articles

Vibration stimulation effect on biomechanical variation of lower-limb joint according to vibration perception threshold

Vibration applied to relaxed muscle or tendon causes tonic reflex contraction in a muscle. Furthermore, when vibration is applied to a muscle, involuntary enhancement of EMG and contraction is induced. Regarding this finding, many studies on the influence of vibration on a muscle and static posture have been performed. However, precedent studies have limitations in applying single characteristic-vibration without any consideration on personal difference on vibration. And studies have been performed to research the change in dynamic state according to the intensity of sensing vibration, but no analysis has been performed on the biomechanical aspect of the lower-limb joints. Nor any consideration was given on the effect of vibration frequency. Therefore, the purpose of this study was to analyze the biomechanical variation in the lower-limb joints according to the characteristics of the mechanical vibration stimulation flowing into Achilles tendon and tibialis anterior tendon during gait, in consideration of the vibration perception threshold and vibration frequency. For this purpose, this study measures the vibration perception threshold according to vibration frequency at each tendon exposed to the stimulation. According to the result, vibration perception threshold varies according to vibrating tendon and vibration frequency. Based on the measurement result of vibration perception threshold, vibration is applied to an Achilles tendon and tibialis anterior tendon during gait. In order to analyze the biomechanical variation in the lower-limb joints according to the characteristics of vibration stimulation applied to each tendon during gait, the angle, moment and power of the lower-limb joints is analyzed using 3D motion analysis system. As a result, biomechanical variation, when vibration lower than a perception threshold is applied, is similar to the variation when vibration at perception threshold is applied. This result implies that vibration stimulation may cause biomechanical variation of lower-limb joints. Furthermore, this means that its biomechanical variation may vary according to the characteristics of the vibration applied.

Analysis of Low Temperature Preheating Effect Based on Battery Temperature-Rise Model

It is difficult to predict the heating time and power consumption associated with the self-heating process of lithium-ion batteries at low temperatures. A temperature-rise model considering the dynamic changes in battery temperature and state of charge is thus proposed. When this model is combined with the ampere-hour integral method, the quantitative relationship among the discharge rate, heating time, and power consumption, during the constant-current discharge process in an internally self-heating battery, is realized. Results show that the temperature-rise model can accurately reflect actual changes in battery temperature. The results indicate that the discharge rate and the heating time present an exponential decreasing trend that is similar to the discharge rate and the power consumption. When a 2 C discharge rate is selected, the battery temperature can rise from −10 °C to 5 °C in 280 s. In this scenario, power consumption of the heating process does not exceed 15% of the rated capacity. As the discharge rate gradually reduced, the heating time and power consumption of the heating process increase slowly. When the discharge rate is 1 C, the heating time is more than 1080 s and the power consumption approaches 30% of the rated capacity. The effect of discharge rate on the heating time and power consumption during the heating process is significantly enhanced when it is less than 1 C.

Vibrational spectroscopic and dielectric properties investigations of phase transitions in KMgPO4 compound

The potassium orthophosphate KMgPO4 with a β-tridymite structure was synthesized via solid-state reaction. X-ray diffraction study confirms the formation of a single phase material which crystallizes at room temperature in monoclinic system. This compound has been investigated by vibrational spectroscopy in the temperature range573–723 K. Thermal analysis shows that this composition undergoes two phase transitions at T1=633Kand T2=693 K.The evolution of Raman line ν and half –width Δν versus temperature introduces huge changes which are associated with the phase transitions originating from the reorientation of the PO4 tetrahedron. Besides, an analysis of the dielectric constants ε′ and ε″versus temperature at several frequencies shows a distribution of relaxation times. This relaxation is probably due to the change in dynamical state of the K+ cation. The ac conductivity behavior can be understood in terms of the motions of K+ cations along the tunnels which are formed by six-membered rings of MgO4 and PO4 tetrahedron linked by common vertices. The activation energies values obtained from the thermal evolution of the conductivity are: Ea1=0.52 eV (T<633 K), Ea2=1.15 eV (633 K <T<693 K) and Ea3=0.96 eV(T>693 K).

Modelling dynamic thermal sensation of human subjects in outdoor environments

Outdoor spaces provide the growing urban population with social, health, environmental, and economic benefits. A thermal comfort model is needed to aid in the design of attractive urban outdoor spaces. In an outdoor environment, a person’s thermal comfort changes with the dynamic weather conditions. However, most of the outdoor thermal comfort models in the literature are for steady-state conditions. To develop a dynamic thermal comfort model, this study observed the responses of 26 human subjects from West Lafayette, Indiana, USA, and Tianjin, China, to a wide range of outdoor thermal environments. The study monitored the subjects’ skin temperatures, recorded their thermal sensations, and measured several outdoor environmental parameters. Analysis of the test data showed that the thermal load, the mean skin temperature, and the change rate of the mean skin temperature of the subjects tested were the most important parameters affecting their thermal comfort in the outdoor spaces. These three parameters were integrated as predictor variables into a comfort model for predicting the outdoor thermal sensation. The model uses the thermal load to evaluate the thermal environment, and the mean skin temperature, and its change rate to consider dynamic changes in the thermal state of the human body. The validity of the model developed in one region was tested with the use of data obtained from the other region.

Behavioral, transcriptomic and epigenetic responses to social challenge in honey bees.

Understanding how social experiences are represented in the brain and shape future responses is a major challenge in the study of behavior. We addressed this problem by studying behavioral, transcriptomic and epigenetic responses to intrusion in honey bees. Previous research showed that initial exposure to an intruder provokes an immediate attack; we now show that this also leads to longer-term changes in behavior in the response to a second intruder, with increases in the probability of responding aggressively and the intensity of aggression lasting 2 and 1 h, respectively. Previous research also documented the whole-brain transcriptomic response; we now show that in the mushroom bodies (MBs) there are 2 waves of gene expression, the first highlighted by genes related to cytoskeleton remodeling, and the second highlighted by genes related to hormones, stress response and transcription factors (TFs). Overall, 16 of 37 (43%) of the TFs whose cis-motifs were enriched in the promoters of the differentially expressed genes (DEGs) were also predicted from transcriptional regulatory network analysis to regulate the MB transcriptional response, highlighting the strong role played by a relatively small subset of TFs in the MB's transcriptomic response to social challenge. Whole brain histone profiling showed few changes in chromatin accessibility in response to social challenge; most DEGs were 'ready' to be activated. These results show how biological embedding of a social challenge involves temporally dynamic changes in the neurogenomic state of a prominent region of the insect brain that are likely to influence future behavior.

Extending HTN to planning and execution control for small combat unit simulation

Modeling how military commanders carry out operations is considered complicated, requiring the capability of not only planning for multiple subordinates but also responding to unexpected events during execution. This paper presents an Hierarchical Task Network (HTN) embedded planning and execution control architecture for small unit commander agents. To be adaptive to dynamic world state changes, the architecture employs a partial planning mechanism and generates actions only applicable to current situations. It is also able to coordinate subordinates’ actions and handle execution failures at runtime. We demonstrate the architecture’s use with an infantry company scenario, where the commander orders three platoons assaulting a defined hill. Our approach shows the effectiveness to control multiple entities in dynamic environments, making the architecture well-suited to represent small unit commanders’ behavior.

NFIB Mediates BRN2 Driven Melanoma Cell Migration and Invasion Through Regulation of EZH2 and MITF

While invasion and metastasis of tumour cells are the principle factor responsible for cancer related deaths, the mechanisms governing the process remain poorly defined. Moreover, phenotypic divergence of sub-populations of tumour cells is known to underpin alternative behaviors linked to tumour progression such as proliferation, survival and invasion. In the context of melanoma, heterogeneity between two transcription factors, BRN2 and MITF, has been associated with phenotypic switching between predominantly invasive and proliferative behaviors respectively. Epigenetic changes, in response to external cues, have been proposed to underpin this process, however the mechanism by which the phenotypic switch occurs is unclear. Here we report the identification of the NFIB transcription factor as a novel downstream effector of BRN2 function in melanoma cells linked to the migratory and invasive characteristics of these cells. Furthermore, the function of NFIB appears to drive an invasive phenotype through an epigenetic mechanism achieved via the upregulation of the polycomb group protein EZH2. A notable target of NFIB mediated up-regulation of EZH2 is decreased MITF expression, which further promotes a less proliferative, more invasive phenotype. Together our data reveal that NFIB has the ability to promote dynamic changes in the chromatin state of melanoma cells to facilitate migration, invasion and metastasis.

Simulation of dynamic changes of methane state based on NMR during coalbed methane output

With anthracite coal of the Qinshui basin as the study object, the effect of water and the displacement pressure on the state of coalbed methane (CBM) during production was studied by combining core flooding with nuclear magnetic resonance (NMR). The adsorption of methane is from larger pores to smaller pores in the adsorption pores. Adsorption and desorption of a dried coal sample follows a logarithmic behavior with time. The process of adsorption is divided into three stages. The adsorption rate increases rapidly in the first stage. The adsorption rate in the initial stage does not correlate to pressure. Meanwhile, the water in the coal reservoir not only hinders the migration of CBM but also reduces the rate of adsorption and desorption. Furthermore, the reversibility of adsorption and desorption is affected. The bottom hole pressure difference plays a dual role during the production of CBM. It can promote the migration of CBM, while hinder its desorption. The control of the bottom hole pressure difference and displacement pressure is very important during CBM continuous output and enhanced CBM recovery. The reasonable range is influenced by the critical desorption pressure, type of reservoir porosity and permeability.

IT troubleshooting with drift analysis in the DevOps era

Over the past few years, DevOps practices have led to many changes in the software industry. The need for agility has resulted in continuous development and deployment of frequent small updates in IT production systems. However, the ever-changing applications and their IT operations environments challenge existing IT troubleshooting approaches, which generally depend on prebuilt domain knowledge and ignore the frequent changes in the DevOps era. Moreover, the complexity and diversity of application architectures exacerbate the challenges. In this paper, we propose an unsupervised learning based drift analysis tool named CHASER to detect and analyze abnormal changes (referred to as “drifts,” which include configuration errors, processes hanging, etc.), with learned change models and patterns in real time as well as in the root cause analysis. First, we categorize the changes into two distinct groups (static and dynamic state changes) and periodically collect the finer grained changes. Then, we extract the time-series and structural features from these changes and apply statistical and machine learning algorithms to learn models and patterns from historical data. Furthermore, we apply these models and patterns to detect drifts in real time and infer possible root causes of reported errors based on a multidimensional correlation approach to improve the precision. Through experiments and case studies, we demonstrate the capability of CHASER.

Non-label immune cell state prediction using Raman spectroscopy.

The acquired immune system, mainly composed of T and B lymphocytes, plays a key role in protecting the host from infection. It is important and technically challenging to identify cell types and their activation status in living and intact immune cells, without staining or killing the cells. Using Raman spectroscopy, we succeeded in discriminating between living T cells and B cells, and visualized the activation status of living T cells without labeling. Although the Raman spectra of T cells and B cells were similar, they could be distinguished by discriminant analysis of the principal components. Raman spectra of activated T cells with anti-CD3 and anti-CD28 antibodies largely differed compared to that of naïve T cells, enabling the prediction of T cell activation status at a single cell level. Our analysis revealed that the spectra of individual T cells gradually change from the pattern of naïve T cells to that of activated T cells during the first 24 h of activation, indicating that changes in Raman spectra reflect slow changes rather than rapid changes in cell state during activation. Our results indicate that the Raman spectrum enables the detection of dynamic changes in individual cell state scattered in a heterogeneous population.

Mitochondrial dynamics following global cerebral ischemia

Global brain ischemia/reperfusion induces neuronal damage in vulnerable brain regions, leading to mitochondrial dysfunction and subsequent neuronal death. Induction of neuronal death is mediated by release of cytochrome c (cyt c) from the mitochondria though a well-characterized increase in outer mitochondrial membrane permeability. However, for cyt c to be released it is first necessary for cyt c to be liberated from the cristae junctions which are gated by Opa1 oligomers. Opa1 has two known functions: maintenance of the cristae junction and mitochondrial fusion. These roles suggest that Opa1 could play a central role in both controlling cyt c release and mitochondrial fusion/fission processes during ischemia/reperfusion. To investigate this concept, we first utilized in vitro real-time imaging to visualize dynamic changes in mitochondria. Oxygen-glucose deprivation (OGD) of neurons grown in culture induced a dual-phase mitochondrial fragmentation profile: (i) fragmentation during OGD with no apoptosis activation, followed by fusion of mitochondrial networks after reoxygenation and a (ii) subsequent extensive fragmentation and apoptosis activation that preceded cell death. We next evaluated changes in mitochondrial dynamic state during reperfusion in a rat model of global brain ischemia. Evaluation of mitochondrial morphology with confocal and electron microscopy revealed a similar induction of fragmentation following global brain ischemia. Mitochondrial fragmentation aligned temporally with specific apoptotic events, including cyt c release, caspase 3/7 activation, and interestingly, release of the fusion protein Opa1. Moreover, we uncovered evidence of loss of Opa1 complexes during the progression of reperfusion, and electron microscopy micrographs revealed a loss of cristae architecture following global brain ischemia. These data provide novel evidence implicating a temporal connection between Opa1 alterations and dysfunctional mitochondrial dynamics following global brain ischemia.

Real-Time Verification of Network Properties Using Atomic Predicates

Network management will benefit from automated tools based upon formal methods. Several such tools have been published in the literature. We present a new formal method for a new tool, Atomic Predicates (AP) Verifier, which is much more time and space efficient than existing tools. Given a set of predicates representing packet filters, AP Verifier computes a set of atomic predicates, which is minimum and unique. The use of atomic predicates dramatically speeds up computation of network reachability. We evaluated the performance of AP Verifier using forwarding tables and ACLs from three large real networks. The atomic predicate sets of these networks were computed very quickly and their sizes are surprisingly small. Real networks are subject to dynamic state changes over time as a result of rule insertion and deletion by protocols and operators, failure and recovery of links and boxes, etc. In a software-defined network, the network state can be observed in real time and thus may be controlled in real time. AP Verifier includes algorithms to process such events and check compliance with network policies and properties in real time. We compare time and space costs of AP Verifier with Header Space and NetPlumber using datasets from the real networks.

Temporal dynamics of arousal and attention in 12-month-old infants.

Research from the animal literature suggests that dynamic, ongoing changes in arousal lead to dynamic changes in an individual's state of anticipatory readiness, influencing how individuals distribute their attention to the environment. However, multiple peripheral indices exist for studying arousal in humans, each showing change on different temporal scales, challenging whether arousal is best characterized as a unitary or a heterogeneous construct. Here, in 53 typical 12-month-olds, we recorded heart rate (HR), head movement patterns, electrodermal activity (EDA), and attention (indexed via look duration) during the presentation of 20 min of mixed animations and TV clips. We also examined triggers for high arousal episodes. Using cross-correlations and auto-correlations, we found that HR and head movement show strong covariance on a sub-minute scale, with changes in head movement consistently preceding changes in HR. EDA showed significant covariance with both, but on much larger time-scales. HR and head movement showed consistent relationships with look duration, but the relationship is temporally specific: relations are observed between head movement, HR and look duration at 30 s time-lag, but not at larger time intervals. No comparable relationships were found for EDA. Changes in head movement and HR occurred before changes in look duration, but not for EDA. Our results suggest that consistent patterns of covariation between heart rate, head movement and EDA can be identified, albeit on different time-scales, and that associations with look duration are present for head movement and heart rate, but not for EDA. Our results suggests that there is a single construct of arousal that can identified across multiple measures, and that phasic changes in arousal precede phasic changes in look duration. © 2016 Wiley Periodicals, Inc. Dev Psychobiol 58: 623-639, 2016.

A Role of Phase-Resetting in Coordinating Large Scale Neural Networks During Attention and Goal-Directed Behavior.

Short periods of oscillatory activation are ubiquitous signatures of neural circuits. A broad range of studies documents not only their circuit origins, but also a fundamental role for oscillatory activity in coordinating information transfer during goal directed behavior. Recent studies suggest that resetting the phase of ongoing oscillatory activity to endogenous or exogenous cues facilitates coordinated information transfer within circuits and between distributed brain areas. Here, we review evidence that pinpoints phase resetting as a critical marker of dynamic state changes of functional networks. Phase resets: (1) set a “neural context” in terms of narrow band frequencies that uniquely characterizes the activated circuits; (2) impose coherent low frequency phases to which high frequency activations can synchronize, identifiable as cross-frequency correlations across large anatomical distances; (3) are critical for neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of canonical E-I circuits that are anatomically ubiquitous. These multiple signatures of phase resets are directly linked to enhanced information transfer and behavioral success. We survey how phase resets re-organize oscillations in diverse task contexts, including sensory perception, attentional stimulus selection, cross-modal integration, Pavlovian conditioning, and spatial navigation. The evidence we consider suggests that phase-resets can drive changes in neural excitability, ensemble organization, functional networks, and ultimately, overt behavior.

Time-lapse electrical impedance spectroscopy for monitoring the cell cycle of single immobilized S. pombe cells.

As a complement and alternative to optical methods, wide-band electrical impedance spectroscopy (EIS) enables multi-parameter, label-free and real-time detection of cellular and subcellular features. We report on a microfluidics-based system designed to reliably capture single rod-shaped Schizosaccharomyces pombe cells by applying suction through orifices in a channel wall. The system enables subsequent culturing of immobilized cells in an upright position, while dynamic changes in cell-cycle state and morphology were continuously monitored through EIS over a broad frequency range. Besides measuring cell growth, clear impedance signals for nuclear division have been obtained. The EIS system has been characterized with respect to sensitivity and detection limits. The spatial resolution in measuring cell length was 0.25 μm, which corresponds to approximately a 5-min interval of cell growth under standard conditions. The comprehensive impedance data sets were also used to determine the occurrence of nuclear division and cytokinesis. The obtained results have been validated through concurrent confocal imaging and plausibilized through comparison with finite-element modeling data. The possibility to monitor cellular and intracellular features of single S. pombe cells during the cell cycle at high spatiotemporal resolution renders the presented microfluidics-based EIS system a suitable tool for dynamic single-cell investigations.

Alpha and gamma oscillation amplitudes synergistically predict the perception of forthcoming nociceptive stimuli.

Ongoing fluctuations of intrinsic cortical networks determine the dynamic state of the brain, and influence the perception of forthcoming sensory inputs. The functional state of these networks is defined by the amplitude and phase of ongoing oscillations of neuronal populations at different frequencies. The contribution of functionally different cortical networks has yet to be elucidated, and only a clear dependence of sensory perception on prestimulus alpha oscillations has been clearly identified. Here, we combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) in a large sample of healthy participants to investigate how ongoing fluctuations in the activity of different cortical networks affect the perception of subsequent nociceptive stimuli. We observed that prestimulus EEG oscillations in the alpha (at bilateral central regions) and gamma (at parietal regions) bands negatively modulated the perception of subsequent stimuli. Combining information about alpha and gamma oscillations predicted subsequent perception significantly more accurately than either measure alone. In a parallel experiment, we found that prestimulus fMRI activity also modulated the perception of subsequent stimuli: perceptual ratings were higher when the BOLD signal was higher in nodes of the sensorimotor network and lower in nodes of the default mode network. Similar to what observed in the EEG data, prediction accuracy was improved when the amplitude of prestimulus BOLD signals in both networks was combined. These findings provide a comprehensive physiological basis to the idea that dynamic changes in brain state determine forthcoming behavioral outcomes. Hum Brain Mapp 37:501–514, 2016. © 2015 Wiley Periodicals, Inc.

Automatic HAZOP analysis method for unsteady operation in chemical based on qualitative simulation and inference

Comparing with continuous production process, unsteady operation process, such as startup and shutdown, tends to abnormal situations due to a large number of operations of operators and dynamic state changes involved. To guarantee a safe operation, process hazard analysis (PHA) is very important to proactively identify the potential safety problems. In the chemical process industry, hazard and operability (HAZOP) analysis is the most widely used method. In this paper, based on proposed qualitative simulation and inference method, an automatic HAZOP analysis method for unsteady operation processes is proposed. Mass transfer and relationships among process variables are expressed by Petri net–directed graph model based fuzzy logic. Operating procedure is expressed according to a formal expression. Possible operation deviations from normal operating procedure are identified by using a group of guidewords. Hazards are identified automatically by qualitative simulation and inference when wrong operation process is performed. The method is validated by a rectification column system.

A Direct Link between Abscisic Acid Sensing and the Chromatin-Remodeling ATPase BRAHMA via Core ABA Signaling Pathway Components

Optimal response to drought is critical for plant survival and will affect biodiversity and crop performance during climate change. Mitotically heritable epigenetic or dynamic chromatin state changes have been implicated in the plant response to the drought stress hormone abscisic acid (ABA). The Arabidopsis SWI/SNF chromatin-remodeling ATPase BRAHMA (BRM) modulates response to ABA by preventing premature activation of stress response pathways during germination. We show that core ABA signaling pathway components physically interact with BRM and post-translationally modify BRM by phosphorylation/dephosphorylation. Genetic evidence suggests that BRM acts downstream of SnRK2.2/2.3 kinases, and biochemical studies identified phosphorylation sites in the C-terminal region of BRM at SnRK2 target sites that are evolutionarily conserved. Finally, the phosphomimetic BRMS1760D S1762D mutant displays ABA hypersensitivity. Prior studies showed that BRM resides at target loci in the ABA pathway in the presence and absence of the stimulus, but is only active in the absence of ABA. Our data suggest that SnRK2-dependent phosphorylation of BRM leads to its inhibition, and PP2CA-mediated dephosphorylation of BRM restores the ability of BRM to repress ABA response. These findings point to the presence of a rapid phosphorylation-based switch to control BRM activity; this property could be potentially harnessed to improve drought tolerance in plants.

Cyclic Intermittent Fasting Influences the Structure of Hepatocyte Nuclear Membrane in Young and Old Rats

Aims: The present study was undertaken to monitor the changes in structural and dynamic state of hepatocyte nuclear membrane of young (3-months) and old (20-months) rats subjected to intermittent fasting (IF). Study Design: young (3-month) and old (20-month) rats were individually housed and randomly assigned to one of five groups (with 10 rats per group): (Control)-fed Ad libitum; (1IF)-provided access to a limited amount of food (4g/100g and 2g/100g of food/body weight for young and old rats, respectively) every other day for 10 days; (1R)-refeeded Ad libitum for 20 days after 1IF; (2IF)provided the same regimen as for 1IF but after successive 1IF and 1R; (2R)-refeeded Ad libitum for 10 days after 2IF. Methodology: The magnitude of fluidity changes was evaluated through measuring the excimer-tomonomer intensity ratio (E/M) in the pyrene emission spectra. The changes in membrane hydration were assessed using Laurdan generalized polarization (GP). Results: During two cycles of intermittent fasting/refeeding statistically significant differences in E/M Original Research Article Girych et al.;JABB, 2(1): 38-50, 2015; Article no.JABB.2015.006 39 for young animals are observed only after the first refeeding (increase by 11% compared to control). 1IF and 1R in old animals were followed by ~26% and ~18% decrease in E/M value. The second cycle of dietary regimen brought about ~20% and ~36% decrease in E/M of old rats after 2IF and 1R, respectively. The first intermittent fasting resulted in ~74% and ~101% increase in GP value of young and old rats, respectively, and the refeeding period GP parameter underwent ~221% and ~89% increase in comparison with control for young and old rats, respectively. After the second IF following the first refeeding the young and old rats were characterized by ~200% and ~44% increase in GP, respectively. On the contrary, second refeeding leads to ~182% and ~27% increase in GP for young and old rats, respectively. Conclusion: The main outcome reached is the identification of differences in the effects of reapplicated IF on nuclear membrane fluidity and hydration in animals of different age, suggesting that membrane responses to IF are governed by age-dependent mechanisms.

The Modified Early Warning Score (MEWS): an instant physiological prognostic indicator of poor outcome in acute pancreatitis.

The Modified Early Warning Score (MEWS) is a bedside scoring system that is non-invasive, simple and repeatable to reflect dynamic changes in physiological state. This study aims to assess accuracy of MEWS and determine an optimal MEWS value in predicting severity in acute pancreatitis (AP). A prospective database of consecutive admissions with AP to a single institution was analysed to determine value of MEWS in identifying severe acute pancreatitis (SAP) and predicting poor outcome. Receiver operator curves (ROC) were used to determine optimal accuracy. Sensitivity, specificity, negative predictive value (NPV), and positive predictive values (PPV) were calculated for the optimal MEWS values obtained. One-hundred and 42 patients with AP were included. The optimal highest MEWS per 24 hours period (hMEWS) and mean MEWS per 24 hour period (mMEWS) in predicting SAP as determined by ROC were 2.5 and 1.625 respectively; with hMEWS ≥3 and mMEWS &gt;1 utilised in this cohort as MEWS scores are whole numbers. On admission, sensitivity, specificity, NPV, PPV, and accuracy of hMEWS ≥3 was 95.5%, 90.8%, 99.0%, 65.6% and 92.0%; and for mMWES &gt;1 was 95.5%, 87.5%, 99.0%, 58.3% and 88.7%, both superior than the Imrie score: 31.5%, 92.1%, 88.9%, 40.0% and 83.5%. The accuracy of hMEWS ≥3 and mMEWS &gt;1 increased over the subsequent 72 hours (days 0-2) from 92 to 96%, and 89% to 94%, respectively. MEWS provides a novel, easy, instant, repeatable, reliable prognostic score that may be superior to existing scoring systems. A larger cohort is required to validate these findings.